Conway's game of life in Python 3 with matplotlib - problem with displaying a formation












1














I am currently trying to program a python 3 implementation of the game of life. My main goal was to display a grid of the size n that gets filled randomly according to conway's rules.
That part works fine.



Now I wanted to implement a second mode that allows you to start with one of the given formations - in my first try a glider.



Here is the main():



import matplotlib.pyplot as plt
import matplotlib.animation as animation
from gol_functions import *

def main():

# get arguments from input function
arguments = input_arguments()
# set the arguments
gridsize = int(arguments.gridsize)
interval = int(arguments.interval)
formation = arguments.formationflag

# if you want to start with a formation:
if formation:
grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
add_glider(1, 1, grid)

# else display a randopm grid
else:
grid = randomgrid(gridsize)

fig, ax = plt.subplots()

# colormap: black -> alive, white -> dead
img = ax.imshow(grid, cmap='binary', interpolation='nearest')

# this will be used to save the animation in a later version
ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
frames=10,
interval=interval,
save_count=50)

# remove x and y - axis labels, numbers and ticks
ax.axes.xaxis.set_ticklabels()
ax.axes.yaxis.set_ticklabels()
plt.xticks()
plt.yticks()

# plot the animated output
plt.show()


if __name__ == '__main__':
main()


Here is the function for adding the glider:



def add_glider(i, j, grid):
"""adds a glider with top-left cell at (i, j)"""
glider = np.array([[0, 0, 255],
[255, 0, 255],
[0, 255, 255]])

grid[i:i+3, j:j+3] = glider


It adds a glider in the grid @ position 1, 1



And here is my update function:



def update(frameNum, img, grid, gridsize):
"""Updates the grid every time it is refreshed"""
newgrid = grid.copy()
for i in range(gridsize):
for j in range(gridsize):
# this formula considers the edge/boundary conditions that appear
# every cell has to have 8 neighbouring cells
# to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
# we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
grid[(i - 1) % gridsize, (j - 1) % gridsize] +
grid[(i - 1) % gridsize, (j + 1) % gridsize] +
grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
(i + 1) % gridsize, (j + 1) % gridsize]) / 255)

# apply conway's basic rules of the game of life for each cell
if grid[i, j] == ON:
if (total < 2) or (total > 3):
newgrid[i, j] = OFF
else:
if total == 3:
newgrid[i, j] = ON
# update data
img.set_data(newgrid)
grid[:] = newgrid[:]
return img,


However when I run it with the option to have it display the glider, all I see is the following formation...



failedglider_1.png



which swiftly turns into this and becomes static:



failedglider_2.png



... instead of an actual glider as seen in the matrix of add_glider. So it seems that somehow the program adds an unwanted alive cell right at the top. I tried to find where it comes from... but I can't find it.



Does anyone have any clues? I am greatful for all help.
Thanks in advance!










share|improve this question





























    1














    I am currently trying to program a python 3 implementation of the game of life. My main goal was to display a grid of the size n that gets filled randomly according to conway's rules.
    That part works fine.



    Now I wanted to implement a second mode that allows you to start with one of the given formations - in my first try a glider.



    Here is the main():



    import matplotlib.pyplot as plt
    import matplotlib.animation as animation
    from gol_functions import *

    def main():

    # get arguments from input function
    arguments = input_arguments()
    # set the arguments
    gridsize = int(arguments.gridsize)
    interval = int(arguments.interval)
    formation = arguments.formationflag

    # if you want to start with a formation:
    if formation:
    grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
    add_glider(1, 1, grid)

    # else display a randopm grid
    else:
    grid = randomgrid(gridsize)

    fig, ax = plt.subplots()

    # colormap: black -> alive, white -> dead
    img = ax.imshow(grid, cmap='binary', interpolation='nearest')

    # this will be used to save the animation in a later version
    ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
    frames=10,
    interval=interval,
    save_count=50)

    # remove x and y - axis labels, numbers and ticks
    ax.axes.xaxis.set_ticklabels()
    ax.axes.yaxis.set_ticklabels()
    plt.xticks()
    plt.yticks()

    # plot the animated output
    plt.show()


    if __name__ == '__main__':
    main()


    Here is the function for adding the glider:



    def add_glider(i, j, grid):
    """adds a glider with top-left cell at (i, j)"""
    glider = np.array([[0, 0, 255],
    [255, 0, 255],
    [0, 255, 255]])

    grid[i:i+3, j:j+3] = glider


    It adds a glider in the grid @ position 1, 1



    And here is my update function:



    def update(frameNum, img, grid, gridsize):
    """Updates the grid every time it is refreshed"""
    newgrid = grid.copy()
    for i in range(gridsize):
    for j in range(gridsize):
    # this formula considers the edge/boundary conditions that appear
    # every cell has to have 8 neighbouring cells
    # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
    # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
    total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
    grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
    grid[(i - 1) % gridsize, (j - 1) % gridsize] +
    grid[(i - 1) % gridsize, (j + 1) % gridsize] +
    grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
    (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

    # apply conway's basic rules of the game of life for each cell
    if grid[i, j] == ON:
    if (total < 2) or (total > 3):
    newgrid[i, j] = OFF
    else:
    if total == 3:
    newgrid[i, j] = ON
    # update data
    img.set_data(newgrid)
    grid[:] = newgrid[:]
    return img,


    However when I run it with the option to have it display the glider, all I see is the following formation...



    failedglider_1.png



    which swiftly turns into this and becomes static:



    failedglider_2.png



    ... instead of an actual glider as seen in the matrix of add_glider. So it seems that somehow the program adds an unwanted alive cell right at the top. I tried to find where it comes from... but I can't find it.



    Does anyone have any clues? I am greatful for all help.
    Thanks in advance!










    share|improve this question



























      1












      1








      1







      I am currently trying to program a python 3 implementation of the game of life. My main goal was to display a grid of the size n that gets filled randomly according to conway's rules.
      That part works fine.



      Now I wanted to implement a second mode that allows you to start with one of the given formations - in my first try a glider.



      Here is the main():



      import matplotlib.pyplot as plt
      import matplotlib.animation as animation
      from gol_functions import *

      def main():

      # get arguments from input function
      arguments = input_arguments()
      # set the arguments
      gridsize = int(arguments.gridsize)
      interval = int(arguments.interval)
      formation = arguments.formationflag

      # if you want to start with a formation:
      if formation:
      grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
      add_glider(1, 1, grid)

      # else display a randopm grid
      else:
      grid = randomgrid(gridsize)

      fig, ax = plt.subplots()

      # colormap: black -> alive, white -> dead
      img = ax.imshow(grid, cmap='binary', interpolation='nearest')

      # this will be used to save the animation in a later version
      ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
      frames=10,
      interval=interval,
      save_count=50)

      # remove x and y - axis labels, numbers and ticks
      ax.axes.xaxis.set_ticklabels()
      ax.axes.yaxis.set_ticklabels()
      plt.xticks()
      plt.yticks()

      # plot the animated output
      plt.show()


      if __name__ == '__main__':
      main()


      Here is the function for adding the glider:



      def add_glider(i, j, grid):
      """adds a glider with top-left cell at (i, j)"""
      glider = np.array([[0, 0, 255],
      [255, 0, 255],
      [0, 255, 255]])

      grid[i:i+3, j:j+3] = glider


      It adds a glider in the grid @ position 1, 1



      And here is my update function:



      def update(frameNum, img, grid, gridsize):
      """Updates the grid every time it is refreshed"""
      newgrid = grid.copy()
      for i in range(gridsize):
      for j in range(gridsize):
      # this formula considers the edge/boundary conditions that appear
      # every cell has to have 8 neighbouring cells
      # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
      # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
      total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
      grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
      grid[(i - 1) % gridsize, (j - 1) % gridsize] +
      grid[(i - 1) % gridsize, (j + 1) % gridsize] +
      grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
      (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

      # apply conway's basic rules of the game of life for each cell
      if grid[i, j] == ON:
      if (total < 2) or (total > 3):
      newgrid[i, j] = OFF
      else:
      if total == 3:
      newgrid[i, j] = ON
      # update data
      img.set_data(newgrid)
      grid[:] = newgrid[:]
      return img,


      However when I run it with the option to have it display the glider, all I see is the following formation...



      failedglider_1.png



      which swiftly turns into this and becomes static:



      failedglider_2.png



      ... instead of an actual glider as seen in the matrix of add_glider. So it seems that somehow the program adds an unwanted alive cell right at the top. I tried to find where it comes from... but I can't find it.



      Does anyone have any clues? I am greatful for all help.
      Thanks in advance!










      share|improve this question















      I am currently trying to program a python 3 implementation of the game of life. My main goal was to display a grid of the size n that gets filled randomly according to conway's rules.
      That part works fine.



      Now I wanted to implement a second mode that allows you to start with one of the given formations - in my first try a glider.



      Here is the main():



      import matplotlib.pyplot as plt
      import matplotlib.animation as animation
      from gol_functions import *

      def main():

      # get arguments from input function
      arguments = input_arguments()
      # set the arguments
      gridsize = int(arguments.gridsize)
      interval = int(arguments.interval)
      formation = arguments.formationflag

      # if you want to start with a formation:
      if formation:
      grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
      add_glider(1, 1, grid)

      # else display a randopm grid
      else:
      grid = randomgrid(gridsize)

      fig, ax = plt.subplots()

      # colormap: black -> alive, white -> dead
      img = ax.imshow(grid, cmap='binary', interpolation='nearest')

      # this will be used to save the animation in a later version
      ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
      frames=10,
      interval=interval,
      save_count=50)

      # remove x and y - axis labels, numbers and ticks
      ax.axes.xaxis.set_ticklabels()
      ax.axes.yaxis.set_ticklabels()
      plt.xticks()
      plt.yticks()

      # plot the animated output
      plt.show()


      if __name__ == '__main__':
      main()


      Here is the function for adding the glider:



      def add_glider(i, j, grid):
      """adds a glider with top-left cell at (i, j)"""
      glider = np.array([[0, 0, 255],
      [255, 0, 255],
      [0, 255, 255]])

      grid[i:i+3, j:j+3] = glider


      It adds a glider in the grid @ position 1, 1



      And here is my update function:



      def update(frameNum, img, grid, gridsize):
      """Updates the grid every time it is refreshed"""
      newgrid = grid.copy()
      for i in range(gridsize):
      for j in range(gridsize):
      # this formula considers the edge/boundary conditions that appear
      # every cell has to have 8 neighbouring cells
      # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
      # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
      total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
      grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
      grid[(i - 1) % gridsize, (j - 1) % gridsize] +
      grid[(i - 1) % gridsize, (j + 1) % gridsize] +
      grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
      (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

      # apply conway's basic rules of the game of life for each cell
      if grid[i, j] == ON:
      if (total < 2) or (total > 3):
      newgrid[i, j] = OFF
      else:
      if total == 3:
      newgrid[i, j] = ON
      # update data
      img.set_data(newgrid)
      grid[:] = newgrid[:]
      return img,


      However when I run it with the option to have it display the glider, all I see is the following formation...



      failedglider_1.png



      which swiftly turns into this and becomes static:



      failedglider_2.png



      ... instead of an actual glider as seen in the matrix of add_glider. So it seems that somehow the program adds an unwanted alive cell right at the top. I tried to find where it comes from... but I can't find it.



      Does anyone have any clues? I am greatful for all help.
      Thanks in advance!







      python python-3.x matplotlib conways-game-of-life






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 23 '18 at 10:36







      Andy M.

















      asked Nov 23 '18 at 7:52









      Andy M.Andy M.

      134




      134
























          1 Answer
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          0














          With some minor fixes to the code from your original post I am able to produce exactly what you wanted. The modified code is listed at the bottom. First frame is shown on the left in the image bellow. After few frames it looks like the image on the right.
          So the glider seems to work just fine :)



          enter image description here



          #!/usr/bin/python
          # call with: python3 cgl.py 10 500 1 1

          import os
          import argparse
          import numpy as np
          import matplotlib.pyplot as plt
          from matplotlib import animation

          ON = 255
          OFF = 0


          def update(frameNum, img, grid, gridsize):
          """Updates the grid every time it is refreshed"""
          newgrid = grid.copy()
          for i in range(gridsize):
          for j in range(gridsize):
          # this formula considers the edge/boundary conditions that appear
          # every cell has to have 8 neighbouring cells
          # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
          # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
          total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
          grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
          grid[(i - 1) % gridsize, (j - 1) % gridsize] +
          grid[(i - 1) % gridsize, (j + 1) % gridsize] +
          grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
          (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

          # apply conway's basic rules of the game of life for each cell
          if grid[i, j] == ON:
          if (total < 2) or (total > 3):
          newgrid[i, j] = OFF
          else:
          if total == 3:
          newgrid[i, j] = ON
          # update data
          grid[:] = newgrid[:]
          img.set_data(newgrid)
          return img,


          def add_glider(i, j, grid):
          """adds a glider with top-left cell at (i, j)"""
          glider = np.array([[0, 0, 255],
          [255, 0, 255],
          [0, 255, 255]])

          grid[i:i+3, j:j+3] = glider


          def main():
          parser = argparse.ArgumentParser(description="Conway's game of life in Python 3")
          parser.add_argument('gridsize', type=int, help='Dimension of grid.')
          parser.add_argument('interval', type=int, help='Interval.')
          parser.add_argument('formationflag', type=bool, help='Predefined formation.')
          parser.add_argument('frame', type=int, help='How many frames to animate.')

          # get arguments from input function
          arguments = parser.parse_args()
          # set the arguments
          frame = int(arguments.frame)
          gridsize = int(arguments.gridsize)
          interval = int(arguments.interval)
          formation = arguments.formationflag

          # if you want to start with a formation:
          if formation:
          grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
          add_glider(1, 1, grid)

          # else display a randopm grid
          else:
          grid = randomgrid(gridsize)

          fig, ax = plt.subplots()

          # colormap: black -> alive, white -> dead
          img = ax.imshow(grid, cmap='binary', interpolation='nearest')

          # # this will be used to save the animation in a later version
          ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
          frames=frame,
          interval=interval,
          save_count=50)

          # remove x and y - axis labels, numbers and ticks
          ax.axes.xaxis.set_ticklabels()
          ax.axes.yaxis.set_ticklabels()
          plt.xticks()
          plt.yticks()

          # plot the animated output
          plt.show()

          if __name__ == '__main__':
          main()
          print("DONE")





          share|improve this answer



















          • 1




            funcAnimation is a function of the matplotlib library animation. Sorry, forgot to include the imports in my post - corrected that. Thanks for looking into it though - now I know that the problem seems to be with the funcAnimation parameters.
            – Andy M.
            Nov 23 '18 at 10:44










          • Oh cool, I have updated the gist code. Now it works and animates the glider nicely. If this solves the problem consider accepting the answer.
            – dsalaj
            Nov 23 '18 at 12:18








          • 1




            Great! Thanks for your effort! I don't quite understand, why it works if you use argument parsing but not if you get the input via a regular "variable = input(xy)" prompt in the command line...
            – Andy M.
            Nov 23 '18 at 13:11










          • @ImportanceOfBeingErnest Good point. The code is now listed in the answer. Thanks. @AndyM. Well not sure why and if that is the case. Only reason why I used argument parsing is because I am familiar with it. I have no idea what your input_arguments does so I couldn't use it. If you return the argument values in correct data type, there should be no problems. I hope it answers your question now.
            – dsalaj
            Nov 23 '18 at 17:03








          • 1




            Thanks! I found the error, There was a problem with my input function. It works now, I marked your question as the solution. Thanks a lot for your help!
            – Andy M.
            Nov 24 '18 at 7:01











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          1 Answer
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          active

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          With some minor fixes to the code from your original post I am able to produce exactly what you wanted. The modified code is listed at the bottom. First frame is shown on the left in the image bellow. After few frames it looks like the image on the right.
          So the glider seems to work just fine :)



          enter image description here



          #!/usr/bin/python
          # call with: python3 cgl.py 10 500 1 1

          import os
          import argparse
          import numpy as np
          import matplotlib.pyplot as plt
          from matplotlib import animation

          ON = 255
          OFF = 0


          def update(frameNum, img, grid, gridsize):
          """Updates the grid every time it is refreshed"""
          newgrid = grid.copy()
          for i in range(gridsize):
          for j in range(gridsize):
          # this formula considers the edge/boundary conditions that appear
          # every cell has to have 8 neighbouring cells
          # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
          # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
          total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
          grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
          grid[(i - 1) % gridsize, (j - 1) % gridsize] +
          grid[(i - 1) % gridsize, (j + 1) % gridsize] +
          grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
          (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

          # apply conway's basic rules of the game of life for each cell
          if grid[i, j] == ON:
          if (total < 2) or (total > 3):
          newgrid[i, j] = OFF
          else:
          if total == 3:
          newgrid[i, j] = ON
          # update data
          grid[:] = newgrid[:]
          img.set_data(newgrid)
          return img,


          def add_glider(i, j, grid):
          """adds a glider with top-left cell at (i, j)"""
          glider = np.array([[0, 0, 255],
          [255, 0, 255],
          [0, 255, 255]])

          grid[i:i+3, j:j+3] = glider


          def main():
          parser = argparse.ArgumentParser(description="Conway's game of life in Python 3")
          parser.add_argument('gridsize', type=int, help='Dimension of grid.')
          parser.add_argument('interval', type=int, help='Interval.')
          parser.add_argument('formationflag', type=bool, help='Predefined formation.')
          parser.add_argument('frame', type=int, help='How many frames to animate.')

          # get arguments from input function
          arguments = parser.parse_args()
          # set the arguments
          frame = int(arguments.frame)
          gridsize = int(arguments.gridsize)
          interval = int(arguments.interval)
          formation = arguments.formationflag

          # if you want to start with a formation:
          if formation:
          grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
          add_glider(1, 1, grid)

          # else display a randopm grid
          else:
          grid = randomgrid(gridsize)

          fig, ax = plt.subplots()

          # colormap: black -> alive, white -> dead
          img = ax.imshow(grid, cmap='binary', interpolation='nearest')

          # # this will be used to save the animation in a later version
          ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
          frames=frame,
          interval=interval,
          save_count=50)

          # remove x and y - axis labels, numbers and ticks
          ax.axes.xaxis.set_ticklabels()
          ax.axes.yaxis.set_ticklabels()
          plt.xticks()
          plt.yticks()

          # plot the animated output
          plt.show()

          if __name__ == '__main__':
          main()
          print("DONE")





          share|improve this answer



















          • 1




            funcAnimation is a function of the matplotlib library animation. Sorry, forgot to include the imports in my post - corrected that. Thanks for looking into it though - now I know that the problem seems to be with the funcAnimation parameters.
            – Andy M.
            Nov 23 '18 at 10:44










          • Oh cool, I have updated the gist code. Now it works and animates the glider nicely. If this solves the problem consider accepting the answer.
            – dsalaj
            Nov 23 '18 at 12:18








          • 1




            Great! Thanks for your effort! I don't quite understand, why it works if you use argument parsing but not if you get the input via a regular "variable = input(xy)" prompt in the command line...
            – Andy M.
            Nov 23 '18 at 13:11










          • @ImportanceOfBeingErnest Good point. The code is now listed in the answer. Thanks. @AndyM. Well not sure why and if that is the case. Only reason why I used argument parsing is because I am familiar with it. I have no idea what your input_arguments does so I couldn't use it. If you return the argument values in correct data type, there should be no problems. I hope it answers your question now.
            – dsalaj
            Nov 23 '18 at 17:03








          • 1




            Thanks! I found the error, There was a problem with my input function. It works now, I marked your question as the solution. Thanks a lot for your help!
            – Andy M.
            Nov 24 '18 at 7:01
















          0














          With some minor fixes to the code from your original post I am able to produce exactly what you wanted. The modified code is listed at the bottom. First frame is shown on the left in the image bellow. After few frames it looks like the image on the right.
          So the glider seems to work just fine :)



          enter image description here



          #!/usr/bin/python
          # call with: python3 cgl.py 10 500 1 1

          import os
          import argparse
          import numpy as np
          import matplotlib.pyplot as plt
          from matplotlib import animation

          ON = 255
          OFF = 0


          def update(frameNum, img, grid, gridsize):
          """Updates the grid every time it is refreshed"""
          newgrid = grid.copy()
          for i in range(gridsize):
          for j in range(gridsize):
          # this formula considers the edge/boundary conditions that appear
          # every cell has to have 8 neighbouring cells
          # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
          # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
          total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
          grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
          grid[(i - 1) % gridsize, (j - 1) % gridsize] +
          grid[(i - 1) % gridsize, (j + 1) % gridsize] +
          grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
          (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

          # apply conway's basic rules of the game of life for each cell
          if grid[i, j] == ON:
          if (total < 2) or (total > 3):
          newgrid[i, j] = OFF
          else:
          if total == 3:
          newgrid[i, j] = ON
          # update data
          grid[:] = newgrid[:]
          img.set_data(newgrid)
          return img,


          def add_glider(i, j, grid):
          """adds a glider with top-left cell at (i, j)"""
          glider = np.array([[0, 0, 255],
          [255, 0, 255],
          [0, 255, 255]])

          grid[i:i+3, j:j+3] = glider


          def main():
          parser = argparse.ArgumentParser(description="Conway's game of life in Python 3")
          parser.add_argument('gridsize', type=int, help='Dimension of grid.')
          parser.add_argument('interval', type=int, help='Interval.')
          parser.add_argument('formationflag', type=bool, help='Predefined formation.')
          parser.add_argument('frame', type=int, help='How many frames to animate.')

          # get arguments from input function
          arguments = parser.parse_args()
          # set the arguments
          frame = int(arguments.frame)
          gridsize = int(arguments.gridsize)
          interval = int(arguments.interval)
          formation = arguments.formationflag

          # if you want to start with a formation:
          if formation:
          grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
          add_glider(1, 1, grid)

          # else display a randopm grid
          else:
          grid = randomgrid(gridsize)

          fig, ax = plt.subplots()

          # colormap: black -> alive, white -> dead
          img = ax.imshow(grid, cmap='binary', interpolation='nearest')

          # # this will be used to save the animation in a later version
          ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
          frames=frame,
          interval=interval,
          save_count=50)

          # remove x and y - axis labels, numbers and ticks
          ax.axes.xaxis.set_ticklabels()
          ax.axes.yaxis.set_ticklabels()
          plt.xticks()
          plt.yticks()

          # plot the animated output
          plt.show()

          if __name__ == '__main__':
          main()
          print("DONE")





          share|improve this answer



















          • 1




            funcAnimation is a function of the matplotlib library animation. Sorry, forgot to include the imports in my post - corrected that. Thanks for looking into it though - now I know that the problem seems to be with the funcAnimation parameters.
            – Andy M.
            Nov 23 '18 at 10:44










          • Oh cool, I have updated the gist code. Now it works and animates the glider nicely. If this solves the problem consider accepting the answer.
            – dsalaj
            Nov 23 '18 at 12:18








          • 1




            Great! Thanks for your effort! I don't quite understand, why it works if you use argument parsing but not if you get the input via a regular "variable = input(xy)" prompt in the command line...
            – Andy M.
            Nov 23 '18 at 13:11










          • @ImportanceOfBeingErnest Good point. The code is now listed in the answer. Thanks. @AndyM. Well not sure why and if that is the case. Only reason why I used argument parsing is because I am familiar with it. I have no idea what your input_arguments does so I couldn't use it. If you return the argument values in correct data type, there should be no problems. I hope it answers your question now.
            – dsalaj
            Nov 23 '18 at 17:03








          • 1




            Thanks! I found the error, There was a problem with my input function. It works now, I marked your question as the solution. Thanks a lot for your help!
            – Andy M.
            Nov 24 '18 at 7:01














          0












          0








          0






          With some minor fixes to the code from your original post I am able to produce exactly what you wanted. The modified code is listed at the bottom. First frame is shown on the left in the image bellow. After few frames it looks like the image on the right.
          So the glider seems to work just fine :)



          enter image description here



          #!/usr/bin/python
          # call with: python3 cgl.py 10 500 1 1

          import os
          import argparse
          import numpy as np
          import matplotlib.pyplot as plt
          from matplotlib import animation

          ON = 255
          OFF = 0


          def update(frameNum, img, grid, gridsize):
          """Updates the grid every time it is refreshed"""
          newgrid = grid.copy()
          for i in range(gridsize):
          for j in range(gridsize):
          # this formula considers the edge/boundary conditions that appear
          # every cell has to have 8 neighbouring cells
          # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
          # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
          total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
          grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
          grid[(i - 1) % gridsize, (j - 1) % gridsize] +
          grid[(i - 1) % gridsize, (j + 1) % gridsize] +
          grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
          (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

          # apply conway's basic rules of the game of life for each cell
          if grid[i, j] == ON:
          if (total < 2) or (total > 3):
          newgrid[i, j] = OFF
          else:
          if total == 3:
          newgrid[i, j] = ON
          # update data
          grid[:] = newgrid[:]
          img.set_data(newgrid)
          return img,


          def add_glider(i, j, grid):
          """adds a glider with top-left cell at (i, j)"""
          glider = np.array([[0, 0, 255],
          [255, 0, 255],
          [0, 255, 255]])

          grid[i:i+3, j:j+3] = glider


          def main():
          parser = argparse.ArgumentParser(description="Conway's game of life in Python 3")
          parser.add_argument('gridsize', type=int, help='Dimension of grid.')
          parser.add_argument('interval', type=int, help='Interval.')
          parser.add_argument('formationflag', type=bool, help='Predefined formation.')
          parser.add_argument('frame', type=int, help='How many frames to animate.')

          # get arguments from input function
          arguments = parser.parse_args()
          # set the arguments
          frame = int(arguments.frame)
          gridsize = int(arguments.gridsize)
          interval = int(arguments.interval)
          formation = arguments.formationflag

          # if you want to start with a formation:
          if formation:
          grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
          add_glider(1, 1, grid)

          # else display a randopm grid
          else:
          grid = randomgrid(gridsize)

          fig, ax = plt.subplots()

          # colormap: black -> alive, white -> dead
          img = ax.imshow(grid, cmap='binary', interpolation='nearest')

          # # this will be used to save the animation in a later version
          ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
          frames=frame,
          interval=interval,
          save_count=50)

          # remove x and y - axis labels, numbers and ticks
          ax.axes.xaxis.set_ticklabels()
          ax.axes.yaxis.set_ticklabels()
          plt.xticks()
          plt.yticks()

          # plot the animated output
          plt.show()

          if __name__ == '__main__':
          main()
          print("DONE")





          share|improve this answer














          With some minor fixes to the code from your original post I am able to produce exactly what you wanted. The modified code is listed at the bottom. First frame is shown on the left in the image bellow. After few frames it looks like the image on the right.
          So the glider seems to work just fine :)



          enter image description here



          #!/usr/bin/python
          # call with: python3 cgl.py 10 500 1 1

          import os
          import argparse
          import numpy as np
          import matplotlib.pyplot as plt
          from matplotlib import animation

          ON = 255
          OFF = 0


          def update(frameNum, img, grid, gridsize):
          """Updates the grid every time it is refreshed"""
          newgrid = grid.copy()
          for i in range(gridsize):
          for j in range(gridsize):
          # this formula considers the edge/boundary conditions that appear
          # every cell has to have 8 neighbouring cells
          # to implement this in a grid of size n we simply fold the 4 edges to each parallel edge
          # we'll end up with a cylinder first, then with a geometric shape called torus (google it.)
          total = int((grid[i, (j - 1) % gridsize] + grid[i, (j + 1) % gridsize] +
          grid[(i - 1) % gridsize, j] + grid[(i + 1) % gridsize, j] +
          grid[(i - 1) % gridsize, (j - 1) % gridsize] +
          grid[(i - 1) % gridsize, (j + 1) % gridsize] +
          grid[(i + 1) % gridsize, (j - 1) % gridsize] + grid[
          (i + 1) % gridsize, (j + 1) % gridsize]) / 255)

          # apply conway's basic rules of the game of life for each cell
          if grid[i, j] == ON:
          if (total < 2) or (total > 3):
          newgrid[i, j] = OFF
          else:
          if total == 3:
          newgrid[i, j] = ON
          # update data
          grid[:] = newgrid[:]
          img.set_data(newgrid)
          return img,


          def add_glider(i, j, grid):
          """adds a glider with top-left cell at (i, j)"""
          glider = np.array([[0, 0, 255],
          [255, 0, 255],
          [0, 255, 255]])

          grid[i:i+3, j:j+3] = glider


          def main():
          parser = argparse.ArgumentParser(description="Conway's game of life in Python 3")
          parser.add_argument('gridsize', type=int, help='Dimension of grid.')
          parser.add_argument('interval', type=int, help='Interval.')
          parser.add_argument('formationflag', type=bool, help='Predefined formation.')
          parser.add_argument('frame', type=int, help='How many frames to animate.')

          # get arguments from input function
          arguments = parser.parse_args()
          # set the arguments
          frame = int(arguments.frame)
          gridsize = int(arguments.gridsize)
          interval = int(arguments.interval)
          formation = arguments.formationflag

          # if you want to start with a formation:
          if formation:
          grid = np.zeros(gridsize*gridsize).reshape(gridsize, gridsize)
          add_glider(1, 1, grid)

          # else display a randopm grid
          else:
          grid = randomgrid(gridsize)

          fig, ax = plt.subplots()

          # colormap: black -> alive, white -> dead
          img = ax.imshow(grid, cmap='binary', interpolation='nearest')

          # # this will be used to save the animation in a later version
          ani = animation.FuncAnimation(fig, update, fargs=(img, grid, gridsize,),
          frames=frame,
          interval=interval,
          save_count=50)

          # remove x and y - axis labels, numbers and ticks
          ax.axes.xaxis.set_ticklabels()
          ax.axes.yaxis.set_ticklabels()
          plt.xticks()
          plt.yticks()

          # plot the animated output
          plt.show()

          if __name__ == '__main__':
          main()
          print("DONE")






          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited Nov 23 '18 at 17:00

























          answered Nov 23 '18 at 10:00









          dsalajdsalaj

          6291027




          6291027








          • 1




            funcAnimation is a function of the matplotlib library animation. Sorry, forgot to include the imports in my post - corrected that. Thanks for looking into it though - now I know that the problem seems to be with the funcAnimation parameters.
            – Andy M.
            Nov 23 '18 at 10:44










          • Oh cool, I have updated the gist code. Now it works and animates the glider nicely. If this solves the problem consider accepting the answer.
            – dsalaj
            Nov 23 '18 at 12:18








          • 1




            Great! Thanks for your effort! I don't quite understand, why it works if you use argument parsing but not if you get the input via a regular "variable = input(xy)" prompt in the command line...
            – Andy M.
            Nov 23 '18 at 13:11










          • @ImportanceOfBeingErnest Good point. The code is now listed in the answer. Thanks. @AndyM. Well not sure why and if that is the case. Only reason why I used argument parsing is because I am familiar with it. I have no idea what your input_arguments does so I couldn't use it. If you return the argument values in correct data type, there should be no problems. I hope it answers your question now.
            – dsalaj
            Nov 23 '18 at 17:03








          • 1




            Thanks! I found the error, There was a problem with my input function. It works now, I marked your question as the solution. Thanks a lot for your help!
            – Andy M.
            Nov 24 '18 at 7:01














          • 1




            funcAnimation is a function of the matplotlib library animation. Sorry, forgot to include the imports in my post - corrected that. Thanks for looking into it though - now I know that the problem seems to be with the funcAnimation parameters.
            – Andy M.
            Nov 23 '18 at 10:44










          • Oh cool, I have updated the gist code. Now it works and animates the glider nicely. If this solves the problem consider accepting the answer.
            – dsalaj
            Nov 23 '18 at 12:18








          • 1




            Great! Thanks for your effort! I don't quite understand, why it works if you use argument parsing but not if you get the input via a regular "variable = input(xy)" prompt in the command line...
            – Andy M.
            Nov 23 '18 at 13:11










          • @ImportanceOfBeingErnest Good point. The code is now listed in the answer. Thanks. @AndyM. Well not sure why and if that is the case. Only reason why I used argument parsing is because I am familiar with it. I have no idea what your input_arguments does so I couldn't use it. If you return the argument values in correct data type, there should be no problems. I hope it answers your question now.
            – dsalaj
            Nov 23 '18 at 17:03








          • 1




            Thanks! I found the error, There was a problem with my input function. It works now, I marked your question as the solution. Thanks a lot for your help!
            – Andy M.
            Nov 24 '18 at 7:01








          1




          1




          funcAnimation is a function of the matplotlib library animation. Sorry, forgot to include the imports in my post - corrected that. Thanks for looking into it though - now I know that the problem seems to be with the funcAnimation parameters.
          – Andy M.
          Nov 23 '18 at 10:44




          funcAnimation is a function of the matplotlib library animation. Sorry, forgot to include the imports in my post - corrected that. Thanks for looking into it though - now I know that the problem seems to be with the funcAnimation parameters.
          – Andy M.
          Nov 23 '18 at 10:44












          Oh cool, I have updated the gist code. Now it works and animates the glider nicely. If this solves the problem consider accepting the answer.
          – dsalaj
          Nov 23 '18 at 12:18






          Oh cool, I have updated the gist code. Now it works and animates the glider nicely. If this solves the problem consider accepting the answer.
          – dsalaj
          Nov 23 '18 at 12:18






          1




          1




          Great! Thanks for your effort! I don't quite understand, why it works if you use argument parsing but not if you get the input via a regular "variable = input(xy)" prompt in the command line...
          – Andy M.
          Nov 23 '18 at 13:11




          Great! Thanks for your effort! I don't quite understand, why it works if you use argument parsing but not if you get the input via a regular "variable = input(xy)" prompt in the command line...
          – Andy M.
          Nov 23 '18 at 13:11












          @ImportanceOfBeingErnest Good point. The code is now listed in the answer. Thanks. @AndyM. Well not sure why and if that is the case. Only reason why I used argument parsing is because I am familiar with it. I have no idea what your input_arguments does so I couldn't use it. If you return the argument values in correct data type, there should be no problems. I hope it answers your question now.
          – dsalaj
          Nov 23 '18 at 17:03






          @ImportanceOfBeingErnest Good point. The code is now listed in the answer. Thanks. @AndyM. Well not sure why and if that is the case. Only reason why I used argument parsing is because I am familiar with it. I have no idea what your input_arguments does so I couldn't use it. If you return the argument values in correct data type, there should be no problems. I hope it answers your question now.
          – dsalaj
          Nov 23 '18 at 17:03






          1




          1




          Thanks! I found the error, There was a problem with my input function. It works now, I marked your question as the solution. Thanks a lot for your help!
          – Andy M.
          Nov 24 '18 at 7:01




          Thanks! I found the error, There was a problem with my input function. It works now, I marked your question as the solution. Thanks a lot for your help!
          – Andy M.
          Nov 24 '18 at 7:01


















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